Final Risk Assessment of Escherichia Coli K-12 Derivatives (PDF)
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Identification of Glucose Non-Fermenting Gram Negative Rods
UK Standards for Microbiology Investigations Identification of Glucose Non-Fermenting Gram Negative Rods REVIEW UNDER Issued by the Standards Unit, Microbiology Services, PHE Bacteriology – Identification | ID 17 | Issue no: 2.2 | Issue date: 11.03.14 | Page: 1 of 24 © Crown copyright 2014 Identification of Glucose Non-Fermenting Gram Negative Rods Acknowledgments UK Standards for Microbiology Investigations (SMIs) are developed under the auspices of Public Health England (PHE) working in partnership with the National Health Service (NHS), Public Health Wales and with the professional organisations whose logos are displayed below and listed on the website http://www.hpa.org.uk/SMI/Partnerships. SMIs are developed, reviewed and revised by various working groups which are overseen by a steering committee (see http://www.hpa.org.uk/SMI/WorkingGroups). The contributions of many individuals in clinical, specialist and reference laboratories who have provided information and comments during the development of this document are acknowledged. We are grateful to the Medical Editors for editing the medical content. For further information please contact us at: Standards Unit Microbiology Services Public Health England 61 Colindale Avenue London NW9 5EQ E-mail: [email protected] Website: http://www.hpa.org.uk/SMI UK Standards for Microbiology Investigations are produced in association with: REVIEW UNDER Bacteriology – Identification | ID 17 | Issue no: 2.2 | Issue date: 11.03.14 | Page: 2 of 24 UK Standards for Microbiology Investigations | Issued by the Standards Unit, Public Health England Identification of Glucose Non-Fermenting Gram Negative Rods Contents ACKNOWLEDGMENTS .......................................................................................................... 2 AMENDMENT TABLE ............................................................................................................. 4 UK STANDARDS FOR MICROBIOLOGY INVESTIGATIONS: SCOPE AND PURPOSE ...... -
E. Coli: Serotypes Other Than O157:H7 Prepared by Zuber Mulla, BA, MSPH DOH, Regional Epidemiologist
E. coli: Serotypes other than O157:H7 Prepared by Zuber Mulla, BA, MSPH DOH, Regional Epidemiologist Escherichia coli (E. coli) is the predominant nonpathogenic facultative flora of the human intestine [1]. However, several strains of E. coli have developed the ability to cause disease in humans. Strains of E. coli that cause gastroenteritis in humans can be grouped into six categories: enteroaggregative (EAEC), enterohemorrhagic (EHEC), enteroinvasive (EIEC), enteropathogenic (EPEC), enterotoxigenic (ETEC), and diffuse adherent (DAEC). Pathogenic E. coli are serotyped on the basis of their O (somatic), H (flagellar), and K (capsular) surface antigen profiles [1]. Each of the six categories listed above has a different pathogenesis and comprises a different set of O:H serotypes [2]. In Florida, gastrointestinal illness caused by E. coli is reportable in two categories: E. coli O157:H7 or E. coli, other. In 1997, 52 cases of E. coli O157:H7 and seven cases of E. coli, other (known serotype), were reported to the Florida Department of Health [3]. Enteroaggregative E. coli (EAEC) - EAEC has been associated with persistent diarrhea (>14 days), especially in developing countries [1]. The diarrhea is usually watery, secretory and not accompanied by fever or vomiting [1]. The incubation period has been estimated to be 20 to 48 hours [2]. Enterohemorrhagic E. coli (EHEC) - While the main EHEC serotype is E. coli O157:H7 (see July 24, 1998, issue of the “Epi Update”), other serotypes such as O111:H8 and O104:H21 are diarrheogenic in humans [2]. EHEC excrete potent toxins called verotoxins or Shiga toxins (so called because of their close resemblance to the Shiga toxin of Shigella dysenteriae 1This group of organisms is often referred to as Shiga toxin-producing E. -
Escherichia Coli
log bio y: O ro p c e i n M A l c Clinical Microbiology: Open a c c i e n s i l s Delmas et al., Clin Microbiol 2015, 4:2 C Access ISSN: 2327-5073 DOI:10.4172/2327-5073.1000195 Commentary Open Access Escherichia coli: The Good, the Bad and the Ugly Julien Delmas*, Guillaume Dalmasso and Richard Bonnet Microbes, Intestine, Inflammation and Host Susceptibility, INSERM U1071, INRA USC2018, Université Clermont Auvergne, Clermont-Ferrand, France *Corresponding author: Julien Delmas, Microbes, Intestine, Inflammation and Host Susceptibility, INSERM U1071, INRA USC2018, Université Clermont Auvergne, Clermont-Ferrand, France, Tel: +334731779; E-mail; [email protected] Received date: March 11, 2015, Accepted date: April 21, 2015, Published date: Aptil 28, 2015 Copyright: © 2015 Delmas J, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Abstract The species Escherichia coli comprises non-pathogenic commensal strains that form part of the normal flora of humans and virulent strains responsible for acute infections inside and outside the intestine. In addition to these pathotypes, various strains of E. coli are suspected of promoting the development or exacerbation of chronic diseases of the intestine such as Crohn’s disease and colorectal cancer. Description replicate within both intestinal epithelial cells and macrophages. These properties were used to define a new pathotype of E. coli designated Escherichia coli is a non-sporeforming, facultatively anaerobic adherent-invasive E. -
Table S4. Phylogenetic Distribution of Bacterial and Archaea Genomes in Groups A, B, C, D, and X
Table S4. Phylogenetic distribution of bacterial and archaea genomes in groups A, B, C, D, and X. Group A a: Total number of genomes in the taxon b: Number of group A genomes in the taxon c: Percentage of group A genomes in the taxon a b c cellular organisms 5007 2974 59.4 |__ Bacteria 4769 2935 61.5 | |__ Proteobacteria 1854 1570 84.7 | | |__ Gammaproteobacteria 711 631 88.7 | | | |__ Enterobacterales 112 97 86.6 | | | | |__ Enterobacteriaceae 41 32 78.0 | | | | | |__ unclassified Enterobacteriaceae 13 7 53.8 | | | | |__ Erwiniaceae 30 28 93.3 | | | | | |__ Erwinia 10 10 100.0 | | | | | |__ Buchnera 8 8 100.0 | | | | | | |__ Buchnera aphidicola 8 8 100.0 | | | | | |__ Pantoea 8 8 100.0 | | | | |__ Yersiniaceae 14 14 100.0 | | | | | |__ Serratia 8 8 100.0 | | | | |__ Morganellaceae 13 10 76.9 | | | | |__ Pectobacteriaceae 8 8 100.0 | | | |__ Alteromonadales 94 94 100.0 | | | | |__ Alteromonadaceae 34 34 100.0 | | | | | |__ Marinobacter 12 12 100.0 | | | | |__ Shewanellaceae 17 17 100.0 | | | | | |__ Shewanella 17 17 100.0 | | | | |__ Pseudoalteromonadaceae 16 16 100.0 | | | | | |__ Pseudoalteromonas 15 15 100.0 | | | | |__ Idiomarinaceae 9 9 100.0 | | | | | |__ Idiomarina 9 9 100.0 | | | | |__ Colwelliaceae 6 6 100.0 | | | |__ Pseudomonadales 81 81 100.0 | | | | |__ Moraxellaceae 41 41 100.0 | | | | | |__ Acinetobacter 25 25 100.0 | | | | | |__ Psychrobacter 8 8 100.0 | | | | | |__ Moraxella 6 6 100.0 | | | | |__ Pseudomonadaceae 40 40 100.0 | | | | | |__ Pseudomonas 38 38 100.0 | | | |__ Oceanospirillales 73 72 98.6 | | | | |__ Oceanospirillaceae -
Characterization of Environmental and Cultivable Antibiotic- Resistant Microbial Communities Associated with Wastewater Treatment
antibiotics Article Characterization of Environmental and Cultivable Antibiotic- Resistant Microbial Communities Associated with Wastewater Treatment Alicia Sorgen 1, James Johnson 2, Kevin Lambirth 2, Sandra M. Clinton 3 , Molly Redmond 1 , Anthony Fodor 2 and Cynthia Gibas 2,* 1 Department of Biological Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA; [email protected] (A.S.); [email protected] (M.R.) 2 Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, NC 28223, USA; [email protected] (J.J.); [email protected] (K.L.); [email protected] (A.F.) 3 Department of Geography & Earth Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA; [email protected] * Correspondence: [email protected]; Tel.: +1-704-687-8378 Abstract: Bacterial resistance to antibiotics is a growing global concern, threatening human and environmental health, particularly among urban populations. Wastewater treatment plants (WWTPs) are thought to be “hotspots” for antibiotic resistance dissemination. The conditions of WWTPs, in conjunction with the persistence of commonly used antibiotics, may favor the selection and transfer of resistance genes among bacterial populations. WWTPs provide an important ecological niche to examine the spread of antibiotic resistance. We used heterotrophic plate count methods to identify Citation: Sorgen, A.; Johnson, J.; phenotypically resistant cultivable portions of these bacterial communities and characterized the Lambirth, K.; Clinton, -
Roper, Hemmons
ORIGINS OF TRANSLOCATIONS IN ASPERGZLLUS NZDULANSl ETTA KAFER Department of Genetics, McGill University, Montreal, Cam& T was realized early in the course of the genetic analysis of the ascomycete ‘Aspergillus nidukns that several of the strains with X-ray induced mutants contain chromosomal aberrations (e.g. two cases mentioned by PONTECORVO, ROPER,HEMMONS, MACDONALD and BUFTON1953). At that time all evidence came from meiotic analysis. In crosses heterozygous for chromosomal aberra- tions, crossing over appears to be reduced since certain unbalanced crossover types show low viability. In fungi, this results in an unusually high frequency of aborted and abnormal ascospores, corresponding to defective pollen in higher plants that show “semisterility” as a result of chromosome aberrations. Ascopore patterns can be used to detect visually the presence of aberrations in Neurospora, either in intact asci (MCCLINTOCK1945), or in random spores (PERKINS, GLASSEYand BLOOM1962). The nonlinear ascus of Aspergillus is too small to make use of this method routinely even though similar patterns have been ob- served in asci from a cross which is now known to have been heterozygous for at least three aberrations (ELLIOTT1960). On the other hand, the discovery of mitotic recombination in Aspergillus (ROPER1952; PONTECORVOand ROPER 1953) has provided new genetic methods not only for the mapping of markers but also for the detection of aberrations, especially translocations (PONTECORVO and =FER 1958; KAFER 1958). Even though most X-ray mutants had been excluded from the general Glasgow stocks, several aberrations have been encountered in the course of mitotic mapping of new markers. The first of these resulted in mitotic linkage between markers of linkage groups I and VII. -
Identification of Genomic Differences Between Laboratory and Commercial
Identification of genomic differences between laboratory and commercial strains of Saccharomyces cerevisiae by Anthony John Heinrich B. Biotech. (Hons) Thesis submitted for the degree of Doctor of Philosophy March 2006 Faculty of Sciences School of Agriculture, Food and Wine Discipline of Wine and Horticulture The University of Adelaide Table of Contents Declaration............................................................................................................................................. i Thesis summary .................................................................................................................................... ii Acknowledgments................................................................................................................................ iv Abbreviations.........................................................................................................................................v CHAPTER 1 Introduction .............................................................................................................1 1.1. INTRODUCTION ....................................................................................................................1 1.2. SIGNAL TRANSDUCTION PATHWAYS ARE ACTIVATED UNDER STRESSFUL CONDITIONS ........2 1.3. THE RESPONSE OF SACCHAROMYCES CEREVISIAE AFTER ENCOUNTERING A STRESSFUL ENVIRONMENT .....................................................................................................................5 1.3.1. Stress related genes........................................................................................................5 -
Microbiology: the Strain in Metagenomics
RESEARCH HIGHLIGHTS MICROBIOLOGY The strain in metagenomics Two computational tools extract strain- His Latent Strain Analysis (LSA) assesses level information from reams of micro- the covariation of short ‘k-mer’ sequences bial sequence data. found in reads, on the basis of a hashing Doctors are well aware that differences function from his search algorithm that between strains of the same bacterial spe- represents all k-mer abundance patterns in cies can have consequences at opposite ends a few gigabytes of fixed memory, regardless of the health-and-disease spectrum. “If you of data size (Cleary et al., 2015). LSA also only look at a species-level annotation, you speeds up the covariation-detection and may end up missing the fact that there are assembly steps. virulence genes in some E. coli strains,” says The advantages are manifold. LSA can Ramnik Xavier of Massachusetts General Stock Photo Alamy discriminate highly related strains, and it Hospital, the Broad Institute and Harvard Microbes from the wild are now being studied at has worked efficiently on four terabytes University. Identifying strains, along with the strain level. of gut microbiome data, whereas other the genetic potential of their genomes, has approaches top out at around 100 gigabytes. become a key goal for computational biolo- tion. Gevers and Xavier say that ConStrains It also found microbes that are missed by gists, but the challenges are compounded shines when it comes to longitudinal stud- traditional assembly because they contrib- by enormous data sets, missing reference ies. The researchers used it to track strains ute few reads to any single sample. -
Shigella and Escherichia Coli at the Crossroads: Machiavellian Masqueraders Or Taxonomic Treachery?
J. Med. Microbiol. Ð Vol. 49 2000), 583±585 # 2000 The Pathological Society of Great Britain and Ireland ISSN 0022-2615 EDITORIAL Shigella and Escherichia coli at the crossroads: machiavellian masqueraders or taxonomic treachery? Shigellae cause an estimated 150 million cases and genera. One authority has even proposed that entero- 600 000 deaths annually, and can cause disease after haemorrhagic E. coli EHEC) such as E. coli O157:H7 ingestion of as few as 10 bacterial cells [1]. They are are essentially `Shigella in a cloak of E. coli antigens' spread by the faecal±oral route, with food, water, [7]. fomites, insects especially ¯ies) and direct person-to- person contact. S. dysenteriae causes brisk and deadly Shigella-like strains of E. coli that cause an invasive, epidemics, particularly in the developing world; S. dysenteric diarrhoeal illness were ®rst described in ¯exneri and S. sonnei account for the endemic form of 1971, over a decade before the appearance in 1982 of the disease, particularly in industrialised nations; S. the new EHEC strains that launched the current wave boydii is rarely encountered [1, 2]. of interest in the E. coli±Shigella connection [8]. Termed `enteroinvasive E. coli' EIEC), these strains, Shigellosis is a locally invasive colitis in which bacteria like shigellae, were able to invade and proliferate invade and proliferate within colonocytes and mucosal within intestinal epithelial cells, eventually causing cell macrophages, trigger apoptosis of macrophages and death [4, 8]. EIEC share with shigellae a c. 140-MDa spread through the mucosa from cell to cell [1]. plasmid pINV) that encodes several outer-membrane Cytokines produced by epithelial cells and macro- proteins involved in invasion of host cells [4, 8]. -
Accurate Differentiation of Escherichia Coli and Shigella Serogroups: Challenges and Strategies
This is a repository copy of Accurate differentiation of Escherichia coli and Shigella serogroups: challenges and strategies. White Rose Research Online URL for this paper: http://eprints.whiterose.ac.uk/157033/ Version: Published Version Article: Devanga Ragupathi, N.K. orcid.org/0000-0001-8667-7132, Muthuirulandi Sethuvel, D.P., Inbanathan, F.Y. et al. (1 more author) (2018) Accurate differentiation of Escherichia coli and Shigella serogroups: challenges and strategies. New Microbes and New Infections, 21. pp. 58-62. ISSN 2052-2975 https://doi.org/10.1016/j.nmni.2017.09.003 Reuse This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs (CC BY-NC-ND) licence. This licence only allows you to download this work and share it with others as long as you credit the authors, but you can’t change the article in any way or use it commercially. More information and the full terms of the licence here: https://creativecommons.org/licenses/ Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing [email protected] including the URL of the record and the reason for the withdrawal request. [email protected] https://eprints.whiterose.ac.uk/ MINI REVIEW Accurate differentiation of Escherichia coli and Shigella serogroups: challenges and strategies N. K. Devanga Ragupathi, D. P. Muthuirulandi Sethuvel, F. Y. Inbanathan and B. Veeraraghavan Department of Clinical Microbiology, Christian Medical College, Vellore, India Abstract Shigella spp. and Escherichia coli are closely related; both belong to the family Enterobacteriaceae. Phenotypically, Shigella spp. -
Wedding Higher Taxonomic Ranks with Metabolic Signatures Coded in Prokaryotic Genomes
Wedding higher taxonomic ranks with metabolic signatures coded in prokaryotic genomes Gregorio Iraola*, Hugo Naya* Corresponding authors: E-mail: [email protected], [email protected] This PDF file includes: Supplementary Table 1 Supplementary Figures 1 to 4 Supplementary Methods SUPPLEMENTARY TABLES Supplementary Tab. 1 Supplementary Tab. 1. Full prediction for the set of 108 external genomes used as test. genome domain phylum class order family genus prediction alphaproteobacterium_LFTY0 Bacteria Proteobacteria Alphaproteobacteria Rhodobacterales Rhodobacteraceae Unknown candidatus_nasuia_deltocephalinicola_PUNC_CP013211 Bacteria Proteobacteria Gammaproteobacteria Unknown Unknown Unknown candidatus_sulcia_muelleri_PUNC_CP013212 Bacteria Bacteroidetes Flavobacteriia Flavobacteriales NA Candidatus Sulcia deinococcus_grandis_ATCC43672_BCMS0 Bacteria Deinococcus-Thermus Deinococci Deinococcales Deinococcaceae Deinococcus devosia_sp_H5989_CP011300 Bacteria Proteobacteria Unknown Unknown Unknown Unknown micromonospora_RV43_LEKG0 Bacteria Actinobacteria Actinobacteria Micromonosporales Micromonosporaceae Micromonospora nitrosomonas_communis_Nm2_CP011451 Bacteria Proteobacteria Betaproteobacteria Nitrosomonadales Nitrosomonadaceae Unknown nocardia_seriolae_U1_BBYQ0 Bacteria Actinobacteria Actinobacteria Corynebacteriales Nocardiaceae Nocardia nocardiopsis_RV163_LEKI01 Bacteria Actinobacteria Actinobacteria Streptosporangiales Nocardiopsaceae Nocardiopsis oscillatoriales_cyanobacterium_MTP1_LNAA0 Bacteria Cyanobacteria NA Oscillatoriales -
Recommended Composition of Influenza Virus Vaccines for Use in the 2020- 2021 Northern Hemisphere Influenza Season February 2020
Recommended composition of influenza virus vaccines for use in the 2020- 2021 northern hemisphere influenza season February 2020 WHO convenes technical consultations1 in February and September each year to recommend viruses for inclusion in influenza vaccines2 for the northern and southern hemisphere influenza seasons, respectively. This recommendation relates to influenza vaccines for use in the forthcoming northern hemisphere 2020-2021 influenza season. A recommendation will be made in September 2020 for vaccines that will be used for the southern hemisphere 2021 influenza season. For countries in tropical and subtropical regions, WHO guidance for choosing between the northern and southern hemisphere formulations is available on the WHO Global Influenza Programme website3. Seasonal influenza activity Between September 2019 and January 2020, influenza activity was reported in all regions, with influenza A(H1N1)pdm09, A(H3N2) and influenza type B viruses co-circulating. In the temperate zone of the northern hemisphere, influenza activity remained at inter- seasonal levels until late October, when it started to increase. In Europe, influenza activity commenced earlier than in recent years and influenza A(H1N1)pdm09, A(H3N2) and type B viruses were reported, although the distribution was not homogeneous. Virus predominance varied between countries. In most countries, influenza activity increased sharply by late January. Countries in North America reported high influenza activity from December, with influenza A and B viruses cocirculating in Canada and the United States of America. In both countries, influenza A(H1N1)pdm09 viruses circulated in higher proportions than A(H3N2) viruses. Generally, countries in East Asia experienced increased influenza activity from late December, with influenza A(H3N2) predominant in China and Mongolia and A(H1N1)pdm09 viruses predominant in Japan and Republic of Korea.